Colon CAR 1.2 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting single or double seed points followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images. Colon CAR 1.2 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the non-enhanced view.
Device Story
Colon CAR 1.2 is a PC-based software tool for CT colonography. It processes CT image data to assist radiologists in identifying and evaluating colonic polyps and lesions. Users define regions of interest (ROI) manually or via semi-automatic seed-point selection with boundary fine-tuning. The device provides 2D/3D visualization and measurement of polyp size and volume. A key feature is the Polyp Enhanced Viewing (PEV) filter, which identifies intra-colonic filling defects protruding into the lumen. The PEV filter is adjustable based on object sphericity, height-to-base ratio (flatness), and diameter range. Results are presented in a Joint Reader view, displaying enhanced and non-enhanced data simultaneously. The software supports simultaneous display of supine and prone images. By highlighting potential polyp candidates, the device aids the radiologist's diagnostic workflow, potentially improving the detection of colonic lesions.
Clinical Evidence
Bench testing only. No clinical data provided.
Technological Characteristics
PC-based, stand-alone software application. Functions as an accessory to CT X-ray systems. Features include 2D/3D visualization, manual/semi-automatic ROI extraction, and Polyp Enhanced Viewing (PEV) filter for feature enhancement.
Indications for Use
Indicated for use by radiologists and clinicians to assist in the evaluation of polyps, cancers, and other lesions in the colon using 2D and 3D CT scan image data.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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# MEDI@SIGHT
K042674
OCT 1 9 2004
Appendix E
### 510(k) SUMMARY OF SAFETY AND EFFECTIVENESS
This summary of safety and effectiveness information is being submitted in accordance with the requirements of 21 CFR 807.92( c ).
| Submitted by: | |
|---------------------|--------------------------------------------|
| Name: | Medicsight PLC. |
| Address: | 46 Berkeley Square<br>London W1J 5AT<br>UK |
| Telephone: | 44 (0) 207 598 4070 |
| Facsimile: | 44 (0) 207 598 4071 |
| Contact: | Carol MacDonald, RA QA Director |
| Date of summary: | 24th September 2004 |
| Device Information: | |
#### evice Information:
| Trade Name: | Colon CAR™ Release 1.2 |
|----------------------|---------------------------------------------|
| Common Name: | Medical imaging software for CT scanners |
| Classification Name: | Computed Tomography X-Ray System, Accessory |
| Regulation Number: | 892.1750 |
#### Predicate Device:
Medicsight Colon CAR 1.2 is substantially equivalent to the following commercially available device:
| Manufacturer | Device | 510(k) No. | Clearance Date |
|--------------|----------------|------------|-------------------|
| MEDICSIGHT | MedicColon 1.0 | K033102 | November 5th 2003 |
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# MEDI®SIGHT
#### Device Description:
Colon CAR™ (Computer Assisted Reader) 1.2 is a software tool designed to assist radiologists and other clinicians in the evaluation of polyps and other lesions in the colon. The software allows the user to select regions of interest either manually or by selecting a single or double seed point, followed by semi-automatic detection of the ROI boundary. It provides 2D and 3D visualisation of polyps and measurement of polyp characteristics such as size and volume. The further feature of Colon CAR™ 1.2 as compared to the cleared device is a Polyp Enhanced Viewing Filter (PEV), the results of which are presented in a Joint Reader filter view (enhanced and non-enhanced data viewed simultaneously). The PEV filter identifies intra-colonic filling defects protruding into the colonic lumen, thereby highlighting potential polyp candidates for further interrogation by the reporting radiologist. This filter is fully adjustable and, in deciding the desired characteristics of the objects to be highlighted, the radiologist may specify the degree of object sphericity (or roundness), the height of the protruding object in relation to its base (object 'flatness') as well as select an approximate object diameter range.
#### Intended Use:
Colon CAR 1.2 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting single or double seed points followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images.
Colon CAR 1.2 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the nonenhanced view.
#### Comparison to Predicate Device:
As in the predicate device, MedicColon 1.0, Colon CAR 1.2 assists users in assessing CT images for the identification and evaluation of colonic polyps.
Test data are provided to validate the performance of the system and its substantial equivalence to the predicate device. The functional features and the intended use of Colon CAR 1.2 are substantially equivalent to the predicate device. The modifications to the original device did not introduce any new potential safety risks.
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# MEDI@SIGHT
### Safety:
A comprehensive hazard analysis was carried out on Colon CAR 1.2, which concluded that any residual risks were as low as reasonably practicable and judged as acceptable when weighed against the intended benefits of use of the system.
### Conclusion:
Colon CAR 1.2 does not raise any new potential safety risks and is equivalent in performance to the existing legally marketed device. Colon CAR 1.2 is therefore substantially equivalent with respect to safety and effectiveness to the predicate device.
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DEPARTMENT OF HEALTH & HUMAN SERVICES
Image /page/3/Picture/1 description: The image is a black and white logo for the U.S. Department of Health & Human Services. The logo features a stylized eagle with its wings spread, and the words "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" are arranged in a circular pattern around the eagle. The eagle is composed of three thick, curved lines that suggest the shape of the bird's body and wings. The text is in a simple, sans-serif font and is evenly spaced around the circle.
Public Health Service
MAR 1 1 2009
Food and Drug Administration 9200 Corporate Boulevard Rockville MD 20850
Ms. Carol MacDonald Regulatory & Quality Director Medicsight 46 Berkeley Square London W1J5AT UNITED KINGDOM
Re: K042674 Trade/Device Name: Medicsight Colon CAR 1.2 Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: NWE Dated: September 27, 2004 Received: September 29, 2004
Dear Ms. MacDonald:
This letter corrects our substantially equivalent letter of October 19, 2004.
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to such additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801; good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The FDA finding os substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Office of Compliance at one of the following numbers, based on the regulation number at the top of this letter.
| 21 CFR 876.xxx | (Gastroenterology/Renal/Urology) | (240) 276-0115 |
|----------------|----------------------------------|----------------|
| 21 CFR 884.xxx | (Obstetrics/Gynecology) | (240) 276-0115 |
| 21 CFR 892.xxx | (Radiology) | (240) 276-0120 |
| Other | | (240) 276-0100 |
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding postmarket surveillance, please contact CDRH's Office of Surveillance and Biometrics' (OSB's) Division of Postmarket Surveillance at 240-276-3474. For questions regarding the reporting of device adverse events (Medical Device Reporting (MDR)), please contact the Division of Surveillance Systems at 240-276-3464. You may obtain other general information on your responsibilities under the Act from the Division of Small Manufactures, International and Consumer Assistance at its toll-free number (800) 638-2041 or (240) 276-3150 or at its Internet address http://www.fda.gov/cdrh/industry.suppot/index.html.
Sincerely yours.
Heike Leuren
Janine M. Morris Acting Director, Division of Reproductive, Abdominal, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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APPENDIX A
Page __ of _
510(k) Number (if known): Ko 4z 2 24
Device Name: Medicsight Colon CAR 1.2
Indications for Use:
Colon CAR 1.2 is a PC-based, stand-alone, non-invasive, image analysis software application for the display and visualization of 2D and 3D medical image data of the colon derived from CT scans, for the purpose of assisting radiologists and other clinicians in the evaluation of polyps, cancers and other lesions. The software provides functionality for the user to extract the region of interest (ROI) either manually using a drawing tool, or "semi-automatically" through the user selecting single or double seed points followed by interactive fine-tuning the boundaries of the ROI. It also allows for the simultaneous display of supine and prone images.
Colon CAR 1.2 contains additional imaging tools which allow enhancement of specified features, and which the clinician can view simultaneously with the non-enhanced view.
## (PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE OF NEEDED)
Concurrence of CDRH, Office of Device Evaluation (ODE)
Nancy C hogdon
Prescription Use_
(Division Sign-Off)
Division of Reproductive, Abdominal,
and Radiological Devices
510(k) Number K042674
3
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
